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Biomedical Engineering and Bioengineering Commons

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Full-Text Articles in Biomedical Engineering and Bioengineering

Differential Patterns Of Theta Activation Underlying Various Cognitive Control Strategies, Jarrod Eisma May 2020

Differential Patterns Of Theta Activation Underlying Various Cognitive Control Strategies, Jarrod Eisma

Biomedical Engineering Undergraduate Honors Theses

In this study, EEG was recorded from 157 participants at the University of Arkansas as they performed three computer tasks that tested inhibitory control (Go/Nogo Task), proactive and reactive control (AX-Continuous Performance Task), and resolving response conflict (Global/Local Task- modified Flanker Task). Time-frequency analysis (ERSP) was the primary focus of this study, in order to take advantage of the temporal and frequential characteristics of EEG recordings. The ERSPs and following statistical analysis showed significantly higher midfrontal theta band (4-8 Hz) power values for target trials (those that required more cognitive control) than control trials, which indicated that the procedure was …


Estimating Cognitive Workload In An Interactive Virtual Reality Environment Using Electrophysiological And Kinematic Activity, Christoph Tremmel Apr 2019

Estimating Cognitive Workload In An Interactive Virtual Reality Environment Using Electrophysiological And Kinematic Activity, Christoph Tremmel

Biomedical Engineering Theses & Dissertations

As virtual reality (VR) technology continues to gain prominence in commercial, educational, recreational and research applications, there is increasing interest in incorporating physiological sensors in VR devices for passive user-state monitoring to eventually increase the sense of immersion. By recording physiological signals such as the electroencephalogram (EEG), electromyography (EMG) or kinematic parameters during the use of a VR device, the user’s interactions in the virtual environment could be adapted in real time based on the user’s cognitive state. This dissertation evaluates the feasibility of passively monitoring cognitive workload via electrophysiological and kinematic activity while performing a classical n-back task in …


Detecting Suicide Risk From Wristworn Activity Tracker Data Using Machine Learning Approaches, Pallavi Atluri Apr 2018

Detecting Suicide Risk From Wristworn Activity Tracker Data Using Machine Learning Approaches, Pallavi Atluri

Electrical Engineering Theses

Suicide is a prevalent cause of death worldwide and depression is a primary concern of many suicidal acts. It is possible that an individual during depression never has any suicidal thoughts at all. On the other hand, some individuals in stable condition with no apparent symptoms of depression feel urges to commit suicide (suicidal ideation). Many such individuals never let anyone know what they are feeling or planning. Suicidal ideation considered an important precursor to suicidal acts.

Detecting the suicide risk in individuals with mood disorders is a major challenge. The current clinical practice to assess suicide risk in these …